Follow-up Comment #2, bug #35187 (project octave):
Sorry I cannot reproduce the problem.
For me, help command works fine.
I have carried out the test windows 7 HomePremium 64 bit.
octave:1> help inv
`inv' is a function from the file
C:OctaveOctave3.4.3_gcc4.5.2liboctave3.4.3octi686-pc-mingw32inv.oct
-- Loadable Function: X = inv (A)
-- Loadable Function: [X, RCOND] = inv (A)
Compute the inverse of the square matrix A. Return an estimate of
the reciprocal condition number if requested, otherwise warn of an
ill-conditioned matrix if the reciprocal condition number is small.
In general it is best to avoid calculating the inverse of a matrix
directly. For example, it is both faster and more accurate to
solve systems of equations (A*x = b) with `Y = A b', rather than
`Y = inv (A) * b'.
If called with a sparse matrix, then in general X will be a full
matrix requiring significantly more storage. Avoid forming the
inverse of a sparse matrix if possible.
See also: ldivide, rdivide
Additional help for built-in functions and operators is
available in the on-line version of the manual. Use the command
`doc <topic>' to search the manual index.
Help and information about Octave is also available on the WWW
at http://www.octave.org and via the address@hidden
mailing list.
octave:2> help fsolve
`fsolve' is a function from the file
C:OctaveOctave3.4.3_gcc4.5.2shareoctave3.4.3moptimizationfsolve.m
-- Function File: fsolve (FCN, X0, OPTIONS)
-- Function File: [X, FVEC, INFO, OUTPUT, FJAC] = fsolve (FCN, ...)
Solve a system of nonlinear equations defined by the function FCN.
FCN should accept a vector (array) defining the unknown variables,
and return a vector of left-hand sides of the equations.
Right-hand sides are defined to be zeros. In other words, this
function attempts to determine a vector X such that `FCN (X)'
gives (approximately) all zeros. X0 determines a starting guess.
The shape of X0 is preserved in all calls to FCN, but otherwise it
is treated as a column vector. OPTIONS is a structure specifying
additional options. Currently, `fsolve' recognizes these options:
`"FunValCheck"', `"OutputFcn"', `"TolX"', `"TolFun"', `"MaxIter"',
`"MaxFunEvals"', `"Jacobian"', `"Updating"', `"ComplexEqn"'
`"TypicalX"', `"AutoScaling"' and `"FinDiffType"'.
If `"Jacobian"' is `"on"', it specifies that FCN, called with 2
output arguments, also returns the Jacobian matrix of right-hand
sides at the requested point. `"TolX"' specifies the termination
tolerance in the unknown variables, while `"TolFun"' is a
tolerance for equations. Default is `1e-7' for both `"TolX"' and
`"TolFun"'.
If `"AutoScaling"' is on, the variables will be automatically
scaled according to the column norms of the (estimated) Jacobian.
As a result, TolF becomes scaling-independent. By default, this
option is off, because it may sometimes deliver unexpected (though
mathematically correct) results.
If `"Updating"' is "on", the function will attempt to use Broyden
updates to update the Jacobian, in order to reduce the amount of
Jacobian calculations. If your user function always calculates
the Jacobian (regardless of number of output arguments), this
option provides no advantage and should be set to false.
`"ComplexEqn"' is `"on"', `fsolve' will attempt to solve complex
equations in complex variables, assuming that the equations
possess a complex derivative (i.e., are holomorphic). If this is
not what you want, should unpack the real and imaginary parts of
the system to get a real system.
For description of the other options, see `optimset'.
On return, FVAL contains the value of the function FCN evaluated
at X, and INFO may be one of the following values:
1
Converged to a solution point. Relative residual error is
less than specified by TolFun.
2
Last relative step size was less that TolX.
3
Last relative decrease in residual was less than TolF.
0
Iteration limit exceeded.
-3
The trust region radius became excessively small.
Note: If you only have a single nonlinear equation of one
variable, using `fzero' is usually a much better idea.
See also: fzero, optimset
Note about user-supplied Jacobians: As an inherent property of the
algorithm, Jacobian is always requested for a solution vector
whose residual vector is already known, and it is the last
accepted successful step. Often this will be one of the last two
calls, but not always. If the savings by reusing intermediate
results from residual calculation in Jacobian calculation are
significant, the best strategy is to employ OutputFcn: After a
vector is evaluated for residuals, if OutputFcn is called with
that vector, then the intermediate results should be saved for
future Jacobian evaluation, and should be kept until a Jacobian
evaluation is requested or until outputfcn is called with a
different vector, in which case they should be dropped in favor of
this most recent vector. A short example how this can be achieved
follows:
function [fvec, fjac] = user_func (x, optimvalues, state)
persistent sav = [], sav0 = [];
if (nargin == 1)
## evaluation call
if (nargout == 1)
sav0.x = x; # mark saved vector
## calculate fvec, save results to sav0.
elseif (nargout == 2)
## calculate fjac using sav.
endif
else
## outputfcn call.
if (all (x == sav0.x))
sav = sav0;
endif
## maybe output iteration status, etc.
endif
endfunction
## ....
fsolve (@user_func, x0, optimset ("OutputFcn", @user_func, ...))
Additional help for built-in functions and operators is
available in the on-line version of the manual. Use the command
`doc <topic>' to search the manual index.
Help and information about Octave is also available on the WWW
at http://www.octave.org and via the address@hidden
mailing list.
_______________________________________________________
Reply to this item at:
<http://savannah.gnu.org/bugs/?35187>
_______________________________________________
Message sent via/by Savannah
http://savannah.gnu.org/